Analysing the injury severity characteristics of urban elderly drivers’ traffic accidents through the generalised ordered logit model: A case of Seoul, South Korea

Abstract

As ageing population is growing faster, traffic accidents involving elderly drivers become a serious social problem in South Korea. The present study aims to examine the impact of environmental characteristics on the injury severity of accidents involving elderly drivers in Seoul, South Korea. To achieve the purpose, the study divided elderly drivers into the following two groups: young-elderly drivers aged 65–69 years and middle- and old-aged drivers over 69 years old. The study also analysed non-elderly drivers aged 30 to 64 years as the comparative group. The study used the generalised ordered logit model, which is widely used to analyse data with ordinal scales. The findings from the study draw attention to the fact that (1) the characteristics of traffic accidents by injury severity considerably differed by age group. (2) risk of accident severity involving elderly drivers increase in areas with heavy traffic volumes and facilities that may create a complex driving condition to elderly drivers, (3) since elderly drivers tend to require longer response time with impaired vision under complex driving environment, it increased the risk of traffic accidents that older drivers face a higher risk of fatal injuries than younger counterparts. Thus, in order to reduce traffic accidents involving elderly drivers, the traffic safety policies should take environmental characteristics as well as the human factor concerning elderly drivers’ difficulties because of ageing and longer cognitive response time. This study contributes to the research in traffic accidents involving elderly drivers in that not only the accident characteristics (human factors, road condition, weather), mostly used for traffic accident analysis, but also environmental factors concerning the urban characteristics of Seoul Metropolitan City were analysed to compare the risk of traffic accidents and accident severity by age groups.

Keywords:

• Elderly drivers
• traffic accidents
• injury severity
• generalised ordered logit model
• crash data

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 The dataset can also be provided through the Traffic Accident Analysis System (http://taas.koroad.or.kr/).

Additional information

Funding

This work was supported by the [Ministry of Education of the Republic of Korea and the National Research Foundation of Korea] under Grant [NRF-2018S1A5A8026776]; and the [Ministry of Education of the Republic of Korea and the National Research Foundation of Korea] under Grant [NRF-2017S1A5A2A02067705]; and this research is the results of the 2020 government [Ministry of Education] funding and support from the Korea Research Foundation [No.5120200113713].